journal article·2025-04-09Open access

Improving Social Acceptance of Orthopedic Foot Orthoses Through Image-Generative AI in Product Design

Stefan Resch, Jakob Schauer, Valentin Schwind, Diana Völz, Daniel Sanchez-Morillo

Applied Sciences· Volume 15· Issue 8

Abstract

The lack of social acceptability for wearable devices such as orthopedic foot orthoses can lead to irregular usage and missed health benefits, as shown in prior studies. While AI-generated designs have been explored for prototyping aesthetic hand orthoses, their impact on social acceptability, particularly for foot orthoses, remains unknown. The current state of research is limited, as no empirical evidence exists on whether AI-designed orthoses influence acceptance, nor has the role of customized generative pre-trained transformers (GPTs) and specific prompting strategies been examined in this context. To address these gaps, we conducted two mixed-methods studies to investigate (1) the impact of AI-generated orthosis designs on social acceptability compared to existing orthopedic products and development concepts and (2) how a customized GPT and different prompt keywords influence acceptance. Our results show that AI-generated designs significantly enhance social acceptance across orthotic categories. Furthermore, we found that personalized GPTs and targeted prompt keywords significantly influence user perception. Overall, our findings highlight the potential of using AI to create socially acceptable design solutions for wearable technology and offer new applications for future smart devices. We contribute to generative AI in product design and provide concrete recommendations for optimizing prompting strategies to enhance social acceptance.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Artificial Intelligence in Healthcare and Education · Digital Imaging in Medicine · Digital Media and Visual Art

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Doctorate Program in Manufacturing, Materials and Environmental Engineering, Doctorate School (EDUCA), University of Cadiz, 11003 Cádiz, Spain

Faculty of Computer Science and Engineering, Frankfurt University of Applied Sciences, 60318 Frankfurt am Main, Germany

Department of Automation Engineering, Electronics and Computer Architecture and Networks, School of Engineering, University of Cadiz, 11519 Cádiz, Spain

Instituto de Investigación e Innovación Biomédica de Cádiz (INiBICA), 11009 Cádiz, Spain

Funding

Hessian Ministry of Science and Art—HMWK, Germany

References (73)

Show source-provided references
1. Enhancing Functional Rehabilitation Through Orthotic Interventions for Foot and Ankle Conditions: A Narrative Review
2. Current concepts review: Orthotics in post-operative foot and ankle surgery
3. Surmen, H.K., Akalan, N.E., and Arslan, Y.Z. (2019). Design, manufacture, and selection of ankle-foot-orthoses. Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction, IGI Global.10.4018/978-1-5225-7368-5.ch020 ↗
4. Design for personalized medicine in orthotics and prosthetics10.1016/j.procir.2019.04.254 ↗
5. User satisfaction with orthotic and prosthetic devices and services of a single clinic10.3109/09638288.2011.641663 ↗
6. Compliance of patients wearing an orthotic device or orthopedic shoes: A systematic review10.1016/j.jbmt.2015.06.008 ↗
7. Ankle-foot orthosis adherence in children and adolescents with cerebral palsy: A scoping review10.1097/PXR.0000000000000095 ↗
8. Dabnichki, P., and Pang, T.Y. (2025). User-Centered Design Framework for Personalized Ankle–Foot Orthoses. Prosthesis, 7.10.3390/prosthesis7010011 ↗
9. Objectively assessed long-term wearing patterns and predictors of wearing orthopaedic footwear in people with diabetes at moderate-to-high risk of foot ulceration: A 12 months observational study10.1186/s13047-023-00656-6 ↗
10. Finco, M.G., Cay, G., Lee, M., Garcia, J., Salazar, E., Tan, T.W., Armstrong, D.G., and Najafi, B. (2023). Taking a Load Off: User Perceptions of Smart Offloading Walkers for Diabetic Foot Ulcers Using the Technology Acceptance Model. Sensors, 23.10.3390/s23052768 ↗
11. Mageshkumar, G., Prasanna, G., Sakthi Priya, G., and Samkilbart, A. (2024, January 14–15). Design of IoT-Based Orthotic Footwear for Lower Limb Correction and Alignment. Proceedings of the 2024 10th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India.10.1109/ICACCS60874.2024.10716926 ↗
12. Imbesi, S., and Scataglini, S. (2021). A User Centered Methodology for the Design of Smart Apparel for Older Users. Sensors, 21.10.3390/s21082804 ↗
13. Users’ perceptions about lower extremity orthotic devices: A systematic review10.1016/j.apmr.2022.10.010 ↗
14. A user-centered qualitative study on experiences with ankle-foot orthoses and suggestions for improved design10.1177/0309364616683981 ↗
15. Adhikari, M.S., Verma, Y.K., Sindhwani, M., and Sachdeva, S. (2025). Generative AI Tools for Product Design and Engineering. Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes, Wiley.10.1002/9781394271078.ch16 ↗
16. Suessmuth, J., Fick, F., and Van Der Vossen, S. (2023). Generative AI for Concept Creation in Footwear Design. Proceedings of the ACM SIGGRAPH 2023 Talks, Association for Computing Machinery.10.1145/3587421.3595416 ↗
17. DALL·E 3 (2025, January 10). OpenAI. Available online: https://openai.com/index/dall-e-3/.
18. Alam, M.F., Lentsch, A., Yu, N., Barmack, S., Kim, S., Acemoglu, D., Hart, J., Johnson, S., and Ahmed, F. (2025, February 10). From Automation to Augmentation: Redefining Engineering Design and Manufacturing in the Age of NextGen-AI. An MIT Exploration of Generative AI. Available online: https://mit-genai.pubpub.org/pub/9s6690gd.10.21428/e4baedd9.e39b392d ↗
19. Sketch2Prototype: Rapid Conceptual Design Exploration and Prototyping with Generative AI10.1017/pds.2024.201 ↗
20. Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A.N., Kaiser, L., and Polosukhin, I. (2017, January 4–9). Attention is all you need. Proceedings of the 31st International Conference on Neural Information Processing Systems (NIPS’17), Red Hook, NY, USA.
21. Exploring the role of text-to-image AI in concept generation10.1017/pds.2023.184 ↗
22. White, J., Fu, Q., Hays, S., Sandborn, M., Olea, C., Gilbert, H., Elnashar, A., Spencer-Smith, J., and Schmidt, D.C. (2023). A prompt pattern catalog to enhance prompt engineering with chatgpt. arXiv.
23. Liu, V., and Chilton, L.B. (May, January 29). Design Guidelines for Prompt Engineering Text-to-Image Generative Models. Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems (CHI ’22), New Orleans, LA, USA.10.1145/3491102.3501825 ↗
24. Generative adversarial networks10.1145/3422622 ↗
25. Chiou, L.Y., Hung, P.K., Liang, R.H., and Wang, C.T. (2023, January 10–14). Designing with AI: An Exploration of Co-Ideation with Image Generators. Proceedings of the 2023 ACM Designing Interactive Systems Conference (DIS ’23), Pittsburgh, PA, USA.10.1145/3563657.3596001 ↗
26. Designing with words: Exploring the integration of text-to-image models in industrial design10.1080/14626268.2024.2411223 ↗
27. Mori, H., and Asahi, Y. The Impact of AI Text-to-Image Generator on Product Styling Design. Proceedings of the Human Interface and the Management of Information.
28. Cai, A., Rick, S.R., Heyman, J.L., Zhang, Y., Filipowicz, A., Hong, M., Klenk, M., and Malone, T. (2023, January 6–9). DesignAID: Using Generative AI and Semantic Diversity for Design Inspiration. Proceedings of the ACM Collective Intelligence Conference (CI ’23), Delft, The Netherlands.10.1145/3582269.3615596 ↗
29. Image generation: A review10.1007/s11063-022-10777-x ↗
30. Exploring the use of ChatGPT and Dall-E for the preliminary design of 3D-printed wrist-hand orthoses
31. Generative Artificial Intelligence in Product Design Education: Navigating Concerns of Originality and Ethics
32. Dunne, L.E., Profita, H., Zeagler, C., Clawson, J., Gilliland, S., Do, E.Y.L., and Budd, J. (2014, January 26–30). The social comfort of wearable technology and gestural interaction. Proceedings of the 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Chicago, IL, USA.10.1109/EMBC.2014.6944540 ↗
33. Sazonov, E., and Neuman, M.R. (2014). Chapter 1.2—Social Aspects of Wearability and Interaction. Wearable Sensors, Academic Press.
34. User acceptance of wearable devices: An extended perspective of perceived value10.1016/j.tele.2015.08.007 ↗
35. Profita, H., Albaghli, R., Findlater, L., Jaeger, P., and Kane, S.K. (2016, January 7–12). The AT Effect: How Disability Affects the Perceived Social Acceptability of Head-Mounted Display Use. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI ’16), San Jose, CA, USA.10.1145/2858036.2858130 ↗
36. The wearer, the device, and its use: Advances in understanding the social acceptability of wearables10.1177/1541931218621237 ↗
37. Exploring the factors that support adoption and sustained use of health and fitness wearables10.1080/0267257X.2016.1234505 ↗
38. Factors and design features influencing the continued use of wearable devices10.1007/s41666-023-00135-4 ↗
39. Factors Influencing the Adoption of Smart Wearable Devices10.1080/10447318.2017.1357902 ↗
40. Revealing insights of users’ perception: An approach to evaluate wearable products based on emotions10.1017/dsj.2020.7 ↗
41. User acceptance of computer technology: A comparison of two theoretical models10.1287/mnsc.35.8.982 ↗
42. User Acceptance of Information Technology: Toward a Unified View10.2307/30036540 ↗
43. Fiske, S.T., Cuddy, A.J., Glick, P., and Xu, J. (2018). A Model of (Often Mixed) Stereotype Content: Competence and Warmth Respectively Follow from Perceived Status and Competition, Routledge.10.4324/9781315187280-7 ↗
44. All the world’s a stage: What makes a wearable socially acceptable10.1145/3137093 ↗
45. Technology acceptance model 3 and a research agenda on interventions10.1111/j.1540-5915.2008.00192.x ↗
46. Kelly, N., and Gilbert, S. (2016, January 7–12). The WEAR Scale: Developing a Measure of the Social Acceptability of a Wearable Device. Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems, San Jose, CA, USA.10.1145/2851581.2892331 ↗
47. Cuddy, A.J., Fiske, S.T., and Glick, P. (2008). Warmth and Competence as Universal Dimensions of Social Perception: The Stereotype Content Model and the BIAS Map, Association for Computing Machinery.10.1016/S0065-2601(07)00002-0 ↗
48. Schwind, V., Deierlein, N., Poguntke, R., and Henze, N. (2019, January 4–9). Understanding the Social Acceptability of Mobile Devices using the Stereotype Content Model. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Glasgow, UK.10.1145/3290605.3300591 ↗
49. Stereotype content model across cultures: Towards universal similarities and some differences10.1348/014466608X314935 ↗
50. Sehrt, J., Braams, B., Henze, N., and Schwind, V. (2022). Social Acceptability in Context: Stereotypical Perception of Shape, Body Location, and Usage of Wearable Devices. Big Data Cogn. Comput., 6.10.3390/bdcc6040100 ↗
51. Profita, H.P., Clawson, J., Gilliland, S., Zeagler, C., Starner, T., Budd, J., and Do, E.Y.L. (2013, January 8–12). Don’t mind me touching my wrist: A case study of interacting with on-body technology in public. Proceedings of the 2013 International Symposium on Wearable Computers, Zurich, Switzerland.10.1145/2493988.2494331 ↗
52. Harrison, C., Lim, B.Y., Shick, A., and Hudson, S.E. (2009). Where to locate wearable displays?: Reaction time performance of visual alerts from tip to toe. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Association for Computing Machinery.10.1145/1518701.1518845 ↗
53. Gemperle, F., Kasabach, C., Stivoric, J., Bauer, M., and Martin, R. (1998, January 19–20). Design for Wearability. Proceedings of the 2nd IEEE International Symposium on Wearable Computers (ISWC ’98), Pittsburgh, PA, USA.
54. (2025, January 10). GPT-4 Is OpenAI’s Most Advanced System, Producing Safer and More Useful Responses. Available online: https://openai.com/index/gpt-4/.
55. OPED-AG (2025, January 10). VACOpedes—Orthese Mit Optimaler Druckentlastung: Für Mittel- und Vorfuß. Available online: https://oped.ch/vacopedes.
56. Enovis (2025, January 10). AIRCAST® AIRSELECT™ Short Walker. Available online: https://www.enovis-medtech.de/AIRCAST-AIRSELECT-Short-Walker.
57. OPED-Medical-Inc. (2025, January 10). VACOcast Diabetic Boot. Available online: https://opedmedical.com/products/vacocast-diabetic/.
58. Enovis (2025, January 10). AIRCAST® AIRSELECT™ Achilles Walker. Available online: https://www.enovis-medtech.de/AIRCAST-AIRSELECT-Achilles-Walker.
59. Berglingstyle (2025, January 10). FastProtect Malleo: Der Sicherheitsgurt für Dein Sprunggelenk. Available online: https://www.berglingstyle.com/products/fastprotect-malleo-5.
60. Betterguards-Technology (2025, January 10). The BetterGuard 1.0: Best Ankle Brace. Available online: https://betterguards.de/en/products/the-betterguard-1.
61. Otto-Bock-HealthCare (2025, January 10). WalkOn Reaction Lateral. Available online: https://www.ottobock.com/en-us/product/28U34.
62. Vitego (2025, January 10). ofa Push Ortho Fußheberorthese AFO. Available online: https://www.vitego-shop.de/bandagen-fuss-ofa-push-ortho-fussheberorthese-afo.
63. Pillai, M. (2025, January 10). Revolutionizing Healing: The Era of 3D-Printed Orthotics. Available online: https://amchronicle.com/case-studies/revolutionizing-healing-the-era-of-3d-printed-orthotics/.
64. HfG Schwäbisch Gmünd (2025, January 10). exoJack—Eine Smarte Orthese für Sprunggelenksbrüche. Available online: https://ausstellung.hfg-gmuend.de/w-2021/projekte/exojack-eine-smarte-orthese-fuer-sprunggelenksbrueche.
65. Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnik IWU (2025, January 10). SensO-FeeT—Sensorisch Aktive Sprunggelenk-Orthese Mit Taktiler Feedback-Technologie. Available online: https://www.iwu.fraunhofer.de/de/projekte/senso-feet-sensorisch-aktive-sprunggelenk-orthese-mit-taktiler-feedback-technologie.html.
66. Taylor, T. (2025, January 10). Sensoria’s Smart Socks Measure Your Running Patterns, Improving Gait. Available online: https://www.si.com/edge/2015/03/06/sensoria-smart-socks-measure-running-patterns.
67. Orthotics, X.P. (2025, January 10). Ankle & Foot. Available online: https://xtremity.ae/ankle-and-foot/.
68. Free3D (2025, January 10). 3D-Gedruckter Orthopädischer Gipsverband am Bein 3D-Modell. Available online: https://free3d.com/de/3d-model/3d-printed-orthopedic-cast-on-leg-7449.html.
69. Using thematic analysis in psychology10.1191/1478088706qp063oa ↗
70. Kassambara, A. (2025, January 10). rstatix: Pipe-Friendly Framework for Basic Statistical Tests. Available online: https://rpkgs.datanovia.com/rstatix/.
71. Schwind, V., and Henze, N. (2020, January 25–29). Anticipated User Stereotypes Systematically Affect the Social Acceptability of Mobile Devices. Proceedings of the 11th Nordic Conference on Human-Computer Interaction: Shaping Experiences (NordiCHI ’20), Tallinn, Estonia.10.1145/3419249.3420113 ↗
72. Minaoglou, P., Tzotzis, A., Efkolidis, N., and Kyratsis, P. (2024). Integrating Artificial Intelligence into the Shoe Design Process. Eng. Proc., 72.10.3390/engproc2024072007 ↗
73. The ethical implications of DALL-E: Opportunities and challenges